The present study aims to optimize the given field treatments to improve the productivity of Brassica and the identification the most influencing agronomic factor among multiple factors. The crop was raised in factorial randomization block design. Three treatments were selected for the present study i.e. genotypes, fertilizer dose and date of sowing. The replicated data was collected for three responses i.e., plant height, oil content and seed yield based on given treatments. The experimental layout was created using a Taguchi Orthogonal Array (OA). L9 orthogonal arrays were chosen for this investigation based on the levels and factors available. The study revealed that out of three treatments, date of sowing is the most influencing factor; however, the genotypes G1 and G2 performed well. The nitrogen requirement has varied results as it depends on performance of genotypes and date of sowing. The research contributes for optimization of resources using Taguchi methods in mustard and concludes that this approach is an easy mathematical approach for the optimization of crop practices in agriculture.